• DocumentCode
    844006
  • Title

    An efficient algorithm and systolic architecture for multiple channel adaptive filtering

  • Author

    Yuen, Stanley M. ; Abend, Kenneth ; Berkowitz, Raymond S.

  • Author_Institution
    RCAS Gov. Electron. Syst. Div., Moorestown, NJ, USA
  • Volume
    36
  • Issue
    5
  • fYear
    1988
  • fDate
    5/1/1988 12:00:00 AM
  • Firstpage
    629
  • Lastpage
    635
  • Abstract
    A multiple-input-multiple-output orthogonalization algorithm and its efficient systolic implementation are presented. The processing architecture is developed using a basic two-input-two-output decorrelation processing element as the primitive building block. Its features are discussed and compared to the approach of K. Gerlach and F.A. Studer (see ibid., vol.AP-34, no.3, p.458-462, 1986) which is based on the modified Gram-Schmidt (MGS) orthogonalization procedure. For simplicity of illustration in the development, batch processing is emphasized. The main features of the newly developed multiple-channel orthogonalization architecture are: (1) it requires no broadcasting of data and any given processing node in the structure only communicates with its neighboring nodes in pipelining fashion; (2) in terms of the total number of arithmetic operations, it is at least as efficient as the MGS approach; (3) the new architecture is developed in a systematic and bottom-up fashion; (4) it is an extremely regular and compact processing structure; (5) no unscrambling of the output channels is needed; and (6) the architecture presented places no restriction on the number of input channels
  • Keywords
    batch processing (computers); cellular arrays; correlation theory; digital filters; filtering and prediction theory; pipeline processing; batch processing; decorrelation processing element; multiple channel adaptive filtering; multiple-input-multiple-output orthogonalisation algorithm; pipelining; processing architecture; processing node; systolic architecture; systolic implementation; Adaptive filters; Convergence; Covariance matrix; Decorrelation; Filtering algorithms; Kalman filters; Least squares approximation; Least squares methods; Resonance light scattering; Signal processing algorithms;
  • fLanguage
    English
  • Journal_Title
    Antennas and Propagation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-926X
  • Type

    jour

  • DOI
    10.1109/8.192139
  • Filename
    192139